Two Student Jobs (m/f/d): R Shiny Apps in the teaching innovation project MultiLa
HTW Berlin is looking for two students to join a project about programming apps for innovative teaching starting as soon as possible at 40 hours per month.
Aim of the project is to build adaptive, interactive learning dashboards using R-Shiny apps to support teaching statistics and data mining. The successful candidate will work with another student and will be supervised by Prof. Dr. Andre Beinrucker (Statistics in Economics) and Prof. Dr. Martin Spott (Data Science in Business Computing).
Complex statistical concepts will be made more accessible with the use of interactive, visual simulations. These support students in applying research-based learning techniques, e.g. exploring statistical models by interacting with them or with underlying data in an application and observing the changes. The simulations will be provided on a web site as so-called R-Shiny-Apps that can be used on a variety of devices like laptops and smartphones.
- Implementation of R-Shiny-Apps based on given specifications, deployment of the Apps
- Evaluation of the apps in teaching
- Analysis of the results using statistics, machine learning an visual analytics
- Experience and interest in programming in the language R and the package R Shiny
- Knowledge of statistics at university level
- Knowledge of Java Script and data bases is advantageous
- Work on innovative and impactful tasks to foster innovative teaching
- Opportunity (and obligation) to broaden your knowledge and skills “on the job” by self-studying, free access to www.datacamp.com, we will share our learnings in the project team
- Possibility to work from home at self-determined working hours
The position will be remunerated based on the students’ pay tariff in Berlin (TV-Stud III- KAV).
Wir freuen uns auf Ihre Bewerbung!
Please send your short CV (1-3 pages) as pdf attached to an e-mail with a few lines about why you would like to join us to Prof. Dr. Andre Beinrucker: firstname.lastname@example.org before October 15. Applications will be evaluated as soon as they are received. We will invite successful applicants to an interview via video conference.